Statistical modelling and forecasting of wheat and meslin export from Ukraine using the singular spectral analysis

Tetyana Chala; Oleksiy Korepanov; Iuliia Lazebnyk; Daryna Chernenko; Georgii Korepanov

doi:https://doi.org/10.59170/stattrans-2023-010

Statistical modelling and forecasting of wheat and meslin export from Ukraine using the singular spectral analysis

Tetyana Chala V. N. Karazin Kharkiv National University. Department of Statistics, Accounting and Auditing, Ukraine. ORCID:http://orcid.org/0000-0001-7499-0308 , Oleksiy Korepanov V. N. Karazin Kharkiv National University. Department of Statistics, Accounting and Auditing, Ukraine. ORCID:http://orcid.org/0000-0002-8499-0819 , Iuliia Lazebnyk V. N. Karazin Kharkiv National University. Department of Statistics, Accounting and Auditing, Ukraine. ORCID:http://orcid.org/0000-0002-2567-9764 , Daryna Chernenko V. N. Karazin Kharkiv National University. Department of Statistics, Accounting and Auditing, Ukraine. ORCID:http://orcid.org/0000-0001-8655-0019 , Georgii Korepanov V. N. Karazin Kharkiv National University. Department of Statistics, Accounting and Auditing, Ukraine. ORCID:http://orcid.org/0000-0001-7724-9339 Statistics in Transition new series, vol. 24, 2023, 1, pages: 169-197 Published online: 24 February 2023 https://doi.org/10.59170/stattrans-2023-010

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ABSTRACT

The article addresses the problems related to the functioning of the worldwide market of wheat and meslin. The authors identify the countries that over the past 17 years have been among the top 10 world leaders in terms of the value of export and import of wheat and meslin. The structure of wheat export by Ukrainian regions is analysed in comparison with the total export. The localisation coefficient is applied to measure the regional unevenness of the distribution of wheat export volumes and the total export by regions of the country. The modelling and forecasting of the volumes and prices of export of wheat and meslin from Ukraine are based on Singular Spectrum Analysis. The study particularly focuses on the individual components of time series, such as trend, annual, semi-annual, four-month, three-month seasonal components. The reliability of the forecast is confirmed by the calculation of the MAPE forecast error and Henry Theil’s inequality coefficient. The article proposes an algorithm for calculating the relative indicators of the structure for the individual components of the reconstructed time series, identified through the singular spectral analysis.

KEYWORDS

export, forecasting, singular spectrum analysis, Ukraine, wheat and meslin.

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